An Empirical Analysis of Forecast Sharing in the Semiconductor Equipment Supply Chain

We study the demand forecast-sharing process between a buyer of customized production equipment and a set of equipment suppliers. Based on a large data collection we undertook in the semiconductor equipment supply chain, we empirically investigate the relationship between the buyer\u27s forecasting behavior and the supplier\u27s delivery performance. The buyer\u27s forecasting behavior is characterized by the frequency and magnitude of forecast revisions it requests (forecast volatility) as well as by the fraction of orders that were forecasted but never actually purchased (forecast inflation). The supplier\u27s delivery performance is measured by its ability to meet delivery dates requested by the customers. Based on a duration analysis, we are able to show that suppliers penalize buyers for unreliable forecasts by providing lower service levels. Vice versa, we also show that buyers penalize suppliers that have a history of poor service by providing them with overly inflated forecasts

Measuring Imputed Cost in the Semiconductor Equipment Supply Chain

We consider the order-fulfillment process of a supplier producing a customized capital good, such as production equipment, commercial aircraft, medical devices, or defense systems. As is common in these industries, prior to receiving a firm purchase order from the customer, the supplier receives a series of shared forecasts, which are called “soft orders.” Facing a stochastic internal manufacturing lead time, the supplier must decide at what time to begin the fulfillment of the order. This decision requires a trade-off between starting too early, leading to potential holding or cancellation costs, and starting too late, leading to potential delay costs. We collect detailed data of shared forecasts, actual purchase orders, production lead times, and delivery dates for a supplier-buyer dyad in the semiconductor equipment supply chain. Under the assumption that the supplier acts rationally, optimally balancing the cancellation, holding, and delay costs, we are able to estimate the corresponding imputed cost parameters based on the observed data. Our estimation results reveal that the supplier perceives the cost of cancellation to be about two times higher and the holding costs to be about three times higher than the delay cost. In other words, the supplier is very conservative when commencing the order fulfillment, which undermines the effectiveness of the overall forecast-sharing mechanism

An Investigation of Buyers’ Forecast Sharing and Ordering Behavior in a Two-Stage Supply Chain

Profitably balancing demand and supply is a continuous challenge for companies under changing market conditions, and the potential benefit of collaboration between supply chain partners cannot be overlooked by any firm who strives to succeed. One of the key elements to successful collaboration is sharing of forecast information between supply chain partners. However, when supply shortage is expected, buyers may inflate order quantities and/or order forecasts to secure sufficient supply. An important question that arises is how the supplier should allocate inventory to customers when shortage exists. Literature shows that certain allocation policies can reduce buyers’ order inflation behavior. However, this has not yet been empirically shown for order forecast inflation behavior, nor incorporating the behavioral aspects of decision makers. In this dissertation, through behavioral experiments using a supply chain simulation game, we investigate the impact of different capacity allocation mechanisms and information disclosures of a supplier on buyers’ forecast sharing and ordering behavior. We first investigate the buyers’ order forecast sharing behavior in a single-suppliertwo- buyer supply chain. Our behavioral study shows that forecast-accuracy based allocation, where the supplier allocates more capacity to the buyer with better forecast accuracy, can significantly improve order forecast accuracy relative to uniform allocation, where the supplier equally allocates capacity to the buyers. Under both policies, particularly uniform allocation, the order forecast accuracy is improved with the supplier’s information disclosure on the policy. Next, we focus on buyers’ ordering behavior, and formulate a single-supplier-single-buyer base-stock inventory model under constrained supply. We validate our analytical results through numerical simulation, which is then extended to the single-supplier-two-buyer case. We next compare the buyers’ optimal decisions from the simulation with the actual decisions in our behavioral study, and find that buyers in the experiment show a significantly lower profit performance ranging from 0.8% to 14.1%. Using structural estimation modeling techniques, we estimate the buyers’ perceived overage/underage cost ratios from the experiment, and conclude by conducting a detailed analysis on the factors that affect buyers’ ordering decisions. In addition to academic contributions, our results provide insights for practitioners to understand buyers’ strategic behavior and help with designing capacity allocation strategies

Integrating supply chains: An investigation of collaborative knowledge transfers

This paper aims to empirically investigate the impact upon performance of explicit knowledge transfer in the integrated supply chain between a manufacturer and its external suppliers and customers. Literature derived hypotheses were evaluated using International Manufacturing Strategy Survey data from 338 companies. Valid and reliable scales were created via confirmatory factor analysis, and effects upon inventory performance tested via regression techniques. Whilst knowledge transfers from upstream and downstream directions were positively related to a manufacturer's performance, knowledge derived from customers was more powerful. Furthermore, integrated knowledge transfer- the combination of knowledge emanating from both suppliers and customers- had the strongest link to performance. The implications for practioners are that integrating knowledge across supply chains could be more far reaching than the exchange of assets, data and information usually considered in supply chain literature. Furthermore the current generalized approach to managing external knowledge is inadequate. This study expands upon existing literature by including directional implications as to which knowledge inflows are most valuable. For academics, this paper supports and extends existing literature by considering the supplier-manufacturer-customer triad in unison. The focus goes beyond asset, data and information exchange towards the leveraging of external knowledge. Relevant perspectives and dimensions were adopted from the knowledge management stream in order to add conceptual depth. Several areas of knowledge-based supply chain research have been identified as potential opportunities for further investigation.Supply Chain; Knowledge Management; Empirical Research:

A Case Study Of E-Supply Chain & Business Process Reengineering Of A Semiconductor Company In Malaysia

Penglibatan e-perniagaan dalam rantaian bekalan telah mewujudkan e-rantaian bekalan yang baru (e-SC) di firma-firma tempatan dan global. Due to globalization and advancement in information technology (IT), companies adopt best practices in e-business and supply chain management to be globally competitive as both are realities and prospects in 21st century

The amplification of the bullwhip effect in the electronics industry under the influence of panic buying

Purpose: The primary purpose of this article is to show the causes and consequences of supply shortages in semiconductors for the automotive and electronics industries in 2021. The subsidiary objectives describe the behaviour of company managers that contributed to this and make proposals for strengthening the resilience of supply chains to demand impulses through their digitization and transparency of information and material flows. The stated objectives are due to the research gap in the impact of panic buying on the bullwhip effect in the supply chains.Method: The study was based on secondary and primary sources. An analysis of secondary data in the form of reports of Polish listed companies producing electronic devices for the years 2019 and 2021 was carried out in terms of inventory turnover. The year 2019 is treated as a base year, i.e., before the Covid-19 pandemic. In contrast, 2021 presents a period when electronic device manufacturers were already experiencing significant delays in semiconductor deliveries. For primary sources, one semiconductor manufacturer and three electronic device manufacturers were interviewed.Findings: The increase in demand for electronic components, extended delivery times and reduced availability has caused electronic device manufacturers to increase their purchases and inventories for fear of production stoppages, further screwing up the demand spiral and component shortages. Decisions to increase inventories were to some extent based on the practice of panic buying and demonstrated a lack of transparency in supply chains.Implications: The author proposes implementing digitalization and transparency in the supply network in place of the practice based on panic buying, which would significantly reduce production downtime for car makers and electronic device manufacturers, as well as the negative financial consequences related to production stoppages and scrapping of obsolete inventory.Keywords: bullwhip effect, panic buying, semiconductor shortage, supply chain disruptions, Covid-19Paper type: Research paperCel: Celem niniejszego artykułu było zbadanie przyczyn i skutków niedoborów w  dostawach półprzewodników dla przemysłu motoryzacyjnego i elektronicznego w  2021 roku, opisanie zachowań menedżerów przedsiębiorstw, które się do tego przyczyniły, a także przedstawienie propozycji wzmocnienia odporności sieci dostaw na impulsy popytowe poprzez ich digitalizację oraz transparentność przepływów informacyjnych i rzeczowych. Metodyka: Badanie oparto na źródłach wtórnych i pierwotnych. Przeprowadzono analizę danych wtórnych w  postaci raportów polskich spółek giełdowych produkujących urządzenia elektroniczne za lata 2019 i 2021 pod kątem rotacji zapasów. Rok 2019 traktowany jest jako bazowy, tj. jeszcze przed pandemią Covid-19. Z kolei rok 2021 prezentuje okres, w którym producenci urządzeń elektronicznych doświadczali już istotnych opóźnień w dostawach półprzewodników. W odniesieniu do źródeł pierwotnych zostały przeprowadzone wywiady z jednym producentem półprzewodników i trzema producentami urządzeń elektronicznych. Wyniki: Wzrost popytu na komponenty elektroniczne, wydłużenie czasów dostaw i ograniczenie ich dostępności spowodowało, iż producenci urządzeń elektronicznych w obawie przed postojami produkcyjnymi zwiększyli swoje zakupy i zapasy, tym bardziej nakręcając spiralę popytu i niedobory komponentów. Decyzje o powiększaniu zapasów w pewnym stopniu opierały się na praktyce dokonywania zakupów w panice i świadczyły o braku transparentności w łańcuchach dostaw. Implikacje: Autor proponuje wdrożenie digitalizacji i transparentności sieci dostaw w miejsce dokonywania zakupów w panice, co w znacznym stopniu zredukowałoby przestoje produkcyjne producentów samochodów i urządzeń elektronicznych, jak również negatywne konsekwencje finansowe związane z postojami produkcyjnymi i złomowaniem przestarzałych zapasów. Słowa kluczowe: efekt byczego bicza, zakupy dokonywane w panice, niedobory półprzewodników, zakłócenia w łańcuchu dostaw, Covid-19 Typ artykułu: Artykuł badawcz

Information Sharing in a Long-Term Supply Chain Relationship: The Role of Customer Review Strategy

In this paper, we study the practice of forecast sharing and supply chain coordination with a game-theoretical model. We find that in a one-shot version of the game, forecasts are not shared truthfully by the customer. The supplier will rationally discount the forecast information in her capacity allocation. This results in Pareto suboptimality for both supply chain parties. However, we show that a more efficient, truth-sharing outcome can emerge as an equilibrium from a long-term relationship. In this equilibrium, forecast information is transmitted truthfully and trusted by the supplier, who in turn allocates the system-optimal capacity. This leaves both the customer and the supplier better-off, compared to the nontruthful-sharing equilibrium. We identify a multiperiod review strategy profile that supports the truthful-sharing equilibrium. The key element of this strategy is that the supplier computes a scoring index of the customer\u27s behavior that is updated over time and used to evaluate if the customer has sufficient incentive to share his private information truthfully in each transaction of the repeated game. Compared to trigger strategies, review strategies are more tolerant but require diligence and more monitoring effort

Leveraging Open-standard Interorganizational Information Systems for Process Adaptability and Alignment: An Empirical Analysis

PurposeThe purpose of this paper is to understand the value creation mechanisms of open-standard inter-organizational information system (OSIOS), which is a key technology to achieve Industry 4.0. Specifically, this study investigates how the internal assimilation and external diffusion of OSIOS help manufactures facilitate process adaptability and alignment in supply chain network.Design/methodology/approachA survey instrument was designed and administrated to collect data for this research. Using three-stage least squares estimation, the authors empirically tested a number of hypothesized relationships based on a sample of 308 manufacturing firms in China.FindingsThe results of the study show that OSIOS can perform as value creation mechanisms to enable process adaptability and alignment. In addition, the impact of OSIOS internal assimilation is inversely U-shaped where the positive effect on process adaptability will become negative after an extremum point is reached.Originality/valueThis study contributes to the existing literature by providing insights on how OSIOS can improve supply chain integration and thus promote the achievement of industry 4.0. By revealing a U-shaped relationship between OSIOS assimilation and process adaptability, this study fills previous research gap by advancing the understanding on the value creation mechanisms of information systems deployment